Biology subjects

van Rooij, S. J. H.

Publications and source records attributed to van Rooij, S. J. H..

5 recordsLinked to original sources

bioRxiv2023

Neural Domains Associated with Substance Use Disorders: A Systematic Review of Neuroimaging Studies

In a framework for substance use concerning trauma, Hien and colleagues suggested three domains: reward salience, executive function, and negative emotionality. In this PRISMA-guided systematic review, we explored the neural correlates of these domains in individuals who use substances with or without trauma exposure. We included 45 studies utilizing tasks of interest in alcohol, tobacco, and cannabis use groups. Greater reward, lesser regulation of inhibitory processes, and mixed findings of negative emotionality processes in individuals who use substances versus controls were found. Specifically, greater orbitofrontal cortex, ventral tegmental area, striatum, amygdala, and hippocampal activation was found in response to reward-related tasks, and reduced activation was found in the inferior frontal gyrus and hippocampus in response to inhibition-related tasks. No studies in trauma-exposed individuals met our review criteria. Future studies examining the role of trauma-related factors are needed and should explore inhibition- and negative-emotionality domains in individuals who use substances to uncover alterations in these domains that place an individual at greater risk for developing SUD.

neuroscience↗

bioRxiv2022

Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

BackgroundThe cerebellum critically contributes to higher-order cognitive and emotional functions such fear learning and memory. Prior research on cerebellar volume in PTSD is scant and has neglected neuroanatomical subdivisions of the cerebellum that differentially map on to motor, cognitive, and affective functions. MethodsWe quantified cerebellar lobule volumes using structural magnetic resonance imaging in 4,215 adults (PTSD n= 1640; Control n=2575) across 40 sites from the from the ENIGMA-PGC PTSD working group. Using a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation, we obtained volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum total and subregional volume in PTSD compared to healthy controls. The Benjamini-Hochberg procedure was used to control the false discovery rate (p-FDR < .05). ResultsPTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume. In addition, people with PTSD showed reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), but also the vermis (VI, VIII), flocculonodular lobe (lobule X), and cerebellar white matter (all p-FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. ConclusionsThese findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in high-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

neuroscience↗

bioRxiv2021

A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Results of neuroimaging datasets aggregated from multiple sites may be biased by site- specific profiles in participants demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,343 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,067 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM were more sensitive to the detection of significant case-control differences in regional cortical thickness (X2(3) = 34.339, p < 0.001), and case-control differences in age-related cortical thinning (X2(3) = 15.128, p = 0.002). Specifically, ComBat-GAM led to larger effect size estimates of cortical thickness reductions (corrected p-values < 0.001), smaller age-appropriate declines (corrected p-values < 0.001), and lower female to male contrast (corrected p-values < 0.001) in cases compared to controls relative to other harmonization methods. Harmonization with ComBat-GAM also led to greater estimates of age-related declines in cortical thickness (corrected p-values < 0.001) in both cases and controls compared to other harmonization methods. Our results support the use of ComBat-GAM for harmonizing cortical thickness data aggregated from multiple sites and scanners to minimize confounds and increase statistical power.

neuroscience↗

bioRxiv2019

Individual Prediction of Psychotherapy Outcome in Posttraumatic Stress Disorder using Neuroimaging Data

ObjectiveTrauma-focused psychotherapy is the first-line treatment for posttraumatic stress disorder (PTSD) but 30-50% of patients do not benefit sufficiently. We investigated whether structural and resting-state functional magnetic resonance imaging (MRI/rs-fMRI) data could distinguish between treatment responders and non-responders on the group and individual level.\n\nMethodsForty-four male veterans with PTSD underwent baseline scanning followed by trauma-focused psychotherapy. Voxel-wise gray matter volumes were extracted from the structural MRI data and resting-state networks (RSNs) were calculated from rs-fMRI data using independent component analysis. Data were used to detect differences between responders and non-responders on the group level using permutation testing, and the single-subject level using Gaussian process classification with cross-validation.\n\nResultsA RSN centered on the bilateral superior frontal gyrus differed between responders and non-responder groups (PFWE < 0.05) while a RSN centered on the pre-supplementary motor area distinguished between responders and non-responders on an individual-level with 81.4% accuracy (P < 0.001, 84.8% sensitivity, 78% specificity and AUC of 0.93). No significant single-subject classification or group differences were observed for gray matter volume.\n\nConclusionsThis proof-of-concept study demonstrates the feasibility of using rs-fMRI to develop neuroimaging biomarkers for treatment response, which could enable personalized treatment of patients with PTSD.

neuroscience↗

bioRxiv2018

Genome wide association study of hippocampal subfield volume in PTSD cases and trauma-exposed controls

Behavioral, structural, and functional neuroimaging have implicated the hippocampus as a critical brain region in PTSD pathogenesis. We conducted a GWAS of hippocampal subfield volumes in a sample of recent military veteran trauma survivors (n=157), including some with PTSD (n=66). Covariates in our analysis included lifetime PTSD diagnosis, sex, intracranial volume, genomic estimates of ancestry, and childhood trauma. Interactions between genetic variants and lifetime PTSD or childhood trauma were interrogated for SNPs with significant main effects. Several genetic associations surpassed correction for multiple testing for several hippocampal subfields, including fimbria, subiculum, cornu ammonis-1(CA1), and hippocampal amygdala transition area (HATA). One association replicated in an independent cohort of civilians with PTSD (rs12880795 in TUNAR with L-HATA volume, p=3.43 x 10-7 in the discovery and p=0.0004 in the replication cohort). However, the most significant association in the discovery data set was between rs6906714 in LINC02571 and R-fimbria volume (p=5.99 x10-8, q=0.0056). Interestingly, the effect of rs6906714 on R-fimbria volume increased with childhood trauma (G*E interaction p=0.022). In addition to variants in long intergenic non-coding RNAs (lincRNAs), we identified SNPs associated with hippocampal subfield volume, which are also quantitative trait loci (QTLs) for genes involved in RNA editing of glutamate receptor subunits (GluRs), oxidative stress, and autoimmune disorders. Genomic regions, some with putative regulatory roles, influence the volume of hippocampal subfields. Neuroimaging phenotypes may offer important insight into the genetic architecture and neurobiological pathways relevant to PTSD, as well as in the identification of potential biomarkers and drug targets for PTSD.

neuroscience↗